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The impact of having a carer on adult health and social care utilisation
across ve settings of care: A matched cohort study
J. Shand
a
,
*
, M. Gomes
a
, S. Morris
b
a
University College London, 1-19 Torrington Place, London WC1E 7HB, United Kingdom
b
University of Cambridge, East Forvie Building, Cambridge Biomedical Campus, Cambridge, CB2 0SR, United Kingdom
ARTICLE INFO
Keywords:
Informal care
Health service utilisation
Health inequalities
Care substitution
ABSTRACT
Introduction: An estimated 6.8 million people are (informal) carers in the UK. The economic value of annual carer
contributions is an estimated .⋅132bn. Reliance on carers appears to be increasing. There is mixed evidence on
whether carers are substitutes for formal care.
This study investigated the association between having a carer and service use patterns across ve care settings
when compared to a matched cohort without a carer.
Materials and Methods: A matched case-control group analysis using person-level data in Barking and Dagenham
(B&D), a London borough in the U.K., to assess the impact of having a carer in terms of the differences in cost-
weighted utilisation relative to a matched control group.
Results: In 2016/17, for adult residents of B&D, having a carer (n =1,295) was associated with 27% increased
cost-weighted utilisation (mean difference of £2,662, CI £1,595, £3,729, p<0.001) compared to a matched cohort
without a carer. 39% of the cost difference was social care.
Conclusions: Findings suggest additional service use induced by carers may dominate any substitution effect.
Having a carer may be a key element in enabling access to services. As such, there may be wider inequalities in
service access for people without a carer. For an ageing society with projections suggesting there will be more
people without carers in the future, these inequalities need to be addressed.
Introduction
Globally, an increasing number of people with long-term conditions
and social care issues are managed at home with support from carers.
Across the UK today, an estimated 6.8 million people are carers, sup-
porting friends and family who are older, disabled or seriously ill [1].
These carers are unpaid and often described as “lay”, “informal” or
“family” carers [2]. In England, the economic value of the contribution
made by carers is an estimated £132 billion a year [1]. This is calculated
using national survey data on hours of care provided [3] and estimates
of unit costs of replacement homecare. Reliance on carers appears to be
increasing, with reductions in council budgets resulting in fewer people
getting access to formal support [4].
The literature on the impact of carers on the care recipient’s health
and social care utilisation is mixed. On the one hand, the estimated
economic value of carer contributions assumes care substitution, by
having a carer people require fewer hours of paid homecare [1]. On the
other hand, having a carer could increase service utilisation as the
individual has an advocate who can facilitate access to services, trans-
port them to appointments, overcome denial that more care is needed
and ensure full care needs are met. Research in Canada found both for
end-of-life patients: having a carer reduced the need for home-based
care services, but increased utilisation of physician and nurse visits
[5]. A review of informal care across nine European countries found care
substitution for unskilled tasks [6]. Research to date highlights the
complexity associated with substitution of care between formal and
informal care services [7, 8] and the different roles the different care
types provide [9]. Regardless, there is alignment that a growing ageing
population alongside reductions in funding for state-funded social care
will lead to a greater reliance on informal care [10].
The NHS in England has a policy commitment to improve identi-
cation of carers and strengthen support for them, in recognition of the
impact being a carer can have on carer’s health and so they can maintain
their caregiving role [11]. This has led to documentation of whether or
not someone is a carer, has a carer or both in primary care health records
using Read Codes [12]. Formal recognition of having a carer can be
* Corresponding author at: UCLPartners ofces, 3rd Floor, 170 Tottenham Court Road, London W1T 7HA, United Kingdom.
E-mail address: jenny.shand@uclpartners.com (J. Shand).
Contents lists available at ScienceDirect
Health policy
journal homepage: www.elsevier.com/locate/healthpol
https://doi.org/10.1016/j.healthpol.2022.104705
Received 8 July 2020; Received in revised form 10 March 2021; Accepted 30 December 2022
Health policy xxx (xxxx) xxx
2
required for the carer to access benets and respite support.
This study aimed to understand if people with a carer have different
levels of service use across ve settings of health and social care when
compared to those who do not have a carer but have matched individual
characteristics.
Materials and methods
A matched case-control group analysis using person-level data to
assess the impact of having a carer in terms of the differences in the cost
of service use across ve settings of care relative to a matched control
group.
Dataset
A subset of a linked dataset in Barking and Dagenham (B&D) was
used. B&D is a densely populated urban borough in London, England,
with 210,700 residents, high levels of deprivation and ethnic diversity.
The primary outcome measures were total cost and setting-level costs for
hospital, primary care, community care, mental health and social care.
The following types of care were included: hospital services (acci-
dent and emergency (A&E) attendances, elective and non-elective
inpatient stays and outpatient appointments); primary care contacts;
prescriptions; community care contacts (home visits, appointments with
community teams including nurses, pharmacists and allied health pro-
fessionals); mental health services (inpatient stays and outpatient ap-
pointments); and social care (weekly care packages which included costs
for crisis intervention, home care, supported living placements, resi-
dential and nursing home placements). The total cost was estimated
from activity data using a combination of national tariffs (for hospital
services), unit costs (for primary, community and mental health), and
weekly commissioned spend (for social care). Data was not available on
self-funded social care, costs for equipment, transport and home adap-
tation. The total cost was calculated by aggregating individual costs
across the ve settings of care.
The exposure variable was taken from the primary care records using
Read Codes that identify if someone has a carer (918F). Carers may be
family members, neighbours or friends. The nature of support or number
of hours was not available. Costs were not assigned to carers’ activities.
Cohort
Adult residents of B&D between 1st April 2016 and 31st March 2017
were the base cohort for the analysis. Those who died or moved out of
B&D before the 1st April 2017 were excluded from the cohort as they
had less than 12 months of activity data, and known increase in
healthcare utilisation at the end of life [13] could bias results. Of the
remaining 114,393 adults, the following individuals were excluded:
•Those who had a carer and were a carer (n ¼101) as the nature of
their care needs could be different given their ability to be a carer.
Spouse carers, a growing cohort [14], were therefore excluded.
•Those who had no carer but were a carer (n ¼861) as the known
associations between being a carer and declined health status [15]
would impact interpretation of results if they were included as
controls.
•Individuals who lived in households with an occupancy of 11 or
more (n ¼1115, which included 33 individuals who had a
carer) were assumed to be in a care home setting and therefore
excluded from both the treatment group and control group as their
health and social care use are likely to be different from those
residing in their own home [16].
The remaining dataset had 112,316 adults, of which 1295 were
documented as having a carer. Table 1 provides a summary of the
characteristics of the 1295 that had a carer.
Matching
People with a carer differ from those who do not (e.g., those with
carers tend to be older and have a greater degree of morbidity), such that
the mean costs of the two groups are not directly comparable (see
Table 2). In this study, we sought to create two comparable groups that
were identical with respect to all observed characteristics, except the
exposure to a carer.
Matching is a long-standing approach to assess treatment effects in
observational research [17]. It involves balancing the distribution of
covariates in the exposed and unexposed groups in order to control for
any systematic differences between these groups and provide unbiased
estimates of treatment effect. It assumes there is no unmeasured con-
founders that are associated with the chances of having a carer and
health care utilisation. In this study, the exposure or “treatment” is
“having a carer”, and the primary outcome of interest is the cost of
health and social care service use overall and for ve settings of care. We
evaluated the effect of having a carer among those with and without a
carer (the average treatment effect (ATE)).
Nearest neighbour matching with a minimum of one match was used
for the analysis. The nearest neighbour was calculated using Mahala-
nobis distance, in which the weights are based on the inverse of the
covariates’ variance–covariance matrix. We matched people on age,
gender, ethnicity, deprivation, BMI category, smoking status, the num-
ber of and prevalence of 16 conditions, housing tenure, benets received
and housing occupancy. This created a matched cohort of 2590, with
1295 that had a carer and 1295 that did not. We conducted robustness
checks using alternative matching approaches, including: 1) exact
matching on all confounders listed above, 2) a combination of nearest
neighbour matching with exact matching on age, and 3) propensity
score matching.
All data processing, matching and analysis were conducted using
Stata version 15.1.
Results
Of the 112,316 individuals included in the analysis, 1295 people had
Table 1
Summary characteristics of the cohort of residents of Barking and Dagenham in
2016/17 who had a carer (n =1295).
•47% 75 years or older with 20% over 85 years
•55% Female, 45% Male
•38% obese or morbidly obese
•61% non-smokers
•68% had 2 or more of 16 long term conditions, 19% had 4 or more
•The most prevalent conditions were Hypertension (46%), Learning disability (26%),
Diabetes (21%)
•53% in receipt of housing benet
•34% lived alone, 55% lived in a 2–4 person household
Table 2
Mean costs for each setting of care for those who have a carer compared with the
full cohort of people who did not have a carer in Barking and Dagenham in
2016/17.
Have a carer
n ¼1295
Do not have a carer
n ¼111,021 T-test result of
the difference
in means
Mean
(£)
Standard
deviation
Mean
(£)
Standard
deviation
Total costs 12,680 20,797 1415 5648 p =0.00
Hospital 1606 3486 542 1680 p =0.00
Primary
care
1014 1292 274 501 p =0.00
Community 2969 9416 334 3254 p =0.00
Mental
health
2499 11,939 142 2644 p =0.00
Social care 4593 11,155 123 1799 p =0.00
J. Shand et al.
Health policy xxx (xxxx) xxx
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a carer and 111,021 people did not. After matching, the balance be-
tween the exposed and unexposed group improved across all variables,
with standardised differences brought within the threshold for mean-
ingful balance (Fig. 1). Standardised differences are calculated by the
difference in means of each covariate between those with a carer (Xt)
and those without (Xc) divided by the standard deviation in the full
matched cohort (SD): (Xt – Xc)/SD. A standard difference of more than
10 has been denoted by some as indicating meaningful imbalance,
smaller values indicate better matches. Some residual imbalance
remained for age and ethnicity.
The ATE was computed to calculate the difference in costs between
exposed and unexposed matched groups. Table 3 shows the results for
the mean difference in total costs and the mean difference in costs by
setting of care.
The mean total cost of service use for those without a carer was
£10,018 (£987 hospital, £823 primary care, £2608 community care,
£2043 mental health and £3557 social care). Having a carer was asso-
ciated with 27% increased total cost of service use (mean difference of
£2662, CI £1595 - £3729, p<0.001) when compared with those without
a carer. The increase in cost was found across all ve care settings. Social
care was the largest contributor, accounting for £1036 (39%) of the
overall cost difference. Mental health cost differences were not statisti-
cally signicant.
Robustness checks (Fig. 2) reported similar differences in costs be-
tween people with a carer and those without, suggesting that the esti-
mated effect of having a carer is relatively robust to the choice of
confounding adjustment approach.
Discussion
Summary of results
For the adult residents of B&D between 1st April 2016 and 31st
March 2017, health and care costs were £2662 (27%) higher for people
registered in their primary care records to have a carer compared to a
comparable group who were not registered as having a carer. Social care
accounted for much of this difference (39%).
Comparison with the literature
There are conicting perspectives in the literature as to whether
having a carer increases or reduces an individual’s health and social care
Fig. 1. The standardised differences for key variables for the full dataset and for the matched cohort. Note: Values within the grey shaded area (between −10 and 10)
denote meaningful balance between the cases and controls. 0: no difference between exposed and unexposed groups, negative values represent variables for which
the effect of the difference between the exposed and the unexposed is reversed.
Table 3
The differences in mean cost by setting for people with a carer vs those without a
carer (controls), matched on age, gender, ethnicity, deprivation, BMI category,
smoking status, the number of LTCs, the prevalence of 16 conditions, housing
tenure, benets received and housing occupancy.
Mean
ATE of having a
carer, £
% of total
cost
95%
CI
p
Total cost 2662 100% 1595 3729 0.00
Hospital 619 23.3% 75 1164 0.03
Primary care 191 7.1% 108 274 0.00
Community 360 13.5% 134 587 0.00
Mental
health
455 17.1% −30 941 0.07
Social care 1036 39.0% 474 1598 0.00
J. Shand et al.
Health policy xxx (xxxx) xxx
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service utilisation. The literature on the different methods to cost the
contribution of informal carers [18] assumes carers provide care sub-
stitution with the presence of a carer replacing the need for formal paid
care. Our ndings, that people without carers have lower costs across all
settings, suggest that if there is care substitution from having a carer,
those without not only do not have the care provided by the informal
carer but they also have lower use of other services, potentially widening
health inequalities.
The literature provides possible explanations for the increased costs
observed for the cared for cohort. Firstly, a caregiver acting as an
advocate for a patient can increase utilisation of some types of care, for
instance by facilitating visits to hospital emergency departments or
helping to overcome denial that more care is needed [19]. Some studies
have found interdependent and potentially conicting patient and
caregiver preferences with regards to service access, with carers more
likely to proactively seek help when the care recipient would not, or to
preference longer active treatment than their care recipient [20, 21]. In
addition, individuals in the Newcastle 85+study reported high health
and functional ability despite signicant levels of disease and impair-
ment [22]. This may lead to different health seeking behaviour for in-
dividuals without a carer and may explain the increased service use for
those with a carer.
Having a carer has been shown to improve the quality of life for the
care recipient [19]. Higher access to services and having an advocate
may contribute to that quality of life. The increased service use observed
for the cared for cohort needs to be assessed in the context of the wider
health and wellbeing outcomes that having a carer provides.
With regards to mental health, the increase in cost was not signi-
cant for people with a carer. This may reect the different nature of
mental health service provision, carers of people with acute mental
health needs may not be registered in primary care records or it may be
reective of the ongoing impact of stigma of mental illnesses in deter-
mining the health-seeking behaviour of the care recipient [23] and their
carer.
Strengths and limitations
A strength of the study was the breadth of services included (ve
settings of care), in particular community services, mental health and
social care. This allowed for a broader picture of the impact of carers on
health and social care costs compared to previous studies.
By using matching, we have sought to minimise any systematic dif-
ferences in observed confounders between individuals exposed and
unexposed to carers. In addition, unlike regression modelling, these
matching approaches make weaker parametric assumptions [24] and
are expected to provide more robust estimates about the effect of carers
on health and social care costs.
There are several limitations to note. Firstly, the analysis identied
people who had carers from primary care records. This is likely to un-
derestimate the number of people with carers. Less than 1% were
identied in the dataset. In B&D, 8.7% of the adult population reported
being informal carers in the 2011 census [25] and 1 in 10 of the adult
population were reported to be carers in April 2019 [26]. One of the
reasons for the low levels of carers identied through primary care is the
uncertainty around the denition of the term “carer”. Extensive litera-
ture shows many carers do not identify themselves as a carer and are
protective of their relationships with the person they care for, seeing
caring as part of their role as a spouse, parent or child and not wanting to
formalise or label the care they provide [27]. The risk to our analysis of
low carer numbers is that the unexposed cases may contain people who
have carers that are not formally registered with primary care, mis-
representing them as controls.
It was not possible to conrm whether or not the recording of having
a carer was missing at random and as such the extent to which it could
introduce selection bias. In addition, those who had been identied as
having a carer may have a higher level of need such that having a carer is
another marker of increased acuity. As such, there may be people who
have a carer who have not been identied in our dataset who have lower
levels of service use. If this is the case, the research ndings may over-
estimate the effect of having a carer on service use as it may be higher
Fig. 2. Output of the robustness checks comparing the mean difference in total costs for people with a carer compared to those without for different match-
ing scenarios.
J. Shand et al.
Health policy xxx (xxxx) xxx
5
levels of need rather than the presence of a carer that are associated with
the increased service use. Whilst the matching process included vari-
ables that attempt to control for the need/health status of individuals
with carers they might not fully capture the full care needs. If need is not
fully captured by the included covariates in the model, the carer variable
may act as a proxy for need. Further investigation with more detailed
information on individual care needs and the nature of care given by the
carer would be necessary to investigate this further.
The role of the carer and the nature of the caring activities can vary
widely. The literature indicates several dimensions of the role of the
carer and the nature of the caring activities that are important markers
of variation; these include the prime reasons for carer support, the
different roles carers provide, the number of hours the carer provides
support, the length of time the individual has had a carer, whether the
carer lived with the care recipient and the characteristics of the carer
(age, gender, education and employment status). The “Personal Social
Services Survey of Adult Carers” conrmed that each of these di-
mensions can vary greatly for carers in the U.K [28]. The dataset we used
did not have access to these dimensions so it could not be adjusted for
them.
Information on other forms of voluntary services or on services in-
dividuals may have paid for privately was not available; this would have
been particularly important for the control group: their reduced service
use could have been due to receiving other forms of care not accounted
for in the dataset. However, the deprivation prole and low average
earnings of households in B&D suggest that the proportion of people
able to self-fund their care is likely to be very low [29].
Further limitations include lack of longitudinal analysis, which could
have provided a greater understanding of whether the differences in
service utilisation between people with a carer and those without
changed over time and the sequencing of service use. Furthermore,
while we have not identied any major factors that could be an
important predictor of health and social care costs that have not been
measured, there may still be unobserved confounding.
Implications
In the UK, much of the discourse on the role of carers rests on the
economic assumption that carers are a substitute for formal care, with an
hour of their time being directly comparable to an hour of a paid carer
[1]. As such, policy priorities are to identify carers, provide them with
information, and support them to continue their care giving role by
addressing their own health and wellbeing needs [30]. With a growing
ageing population, it is anticipated that the need for care will continue to
grow and supporting carers to continue to deliver caregiving will reduce
the burden on the care system. The ndings of this research challenge
some of these assumptions as individuals with carers were found to have
higher health and social care costs than those without. This raises
questions on the relationship between informal care and the formal care
system. The project did not attempt to conduct a full impact assessment
of carers but rather to understand the impact that having a carer has on
an individual’s health and social care utilisation. The increased costs
across all settings of care suggest that carers do not provide care sub-
stitution of the tasks and activities completed by the health and social
care system or, or perhaps, that additional service use induced by the
carer may dominate any substitution effect. If there was care substitu-
tion, we may have expected to see reduced service use in social care, and
potentially community care settings, for people with a carer where some
of the tasks can be completed by an unskilled workforce. The informal
carers may be lling unmet needs, such as coordinating care, advocating
for the care recipient, providing emotional and social support, all of
which may have a positive impact on the quality of life of the person
being cared for.
There is an opportunity to reect on the relationship between carers
and the formal care system and identify interventions that could support
more care substitution. This may include providing bespoke training and
education and seeing carers as an extension of the care workforce. Over
the past decade, patient education for self-care has become a core
function of the NHS, recognising that an individual spends more time
caring for themselves than interacting with health and care pro-
fessionals. The same logic may be applied to carers. However, carer
education is largely delivered by the voluntary sector and as yet has not
become an explicit role of the NHS, despite the potential for impact.
Health inequalities are a growing challenge for all societies and are
of global concern, although the magnitude of the problem varies across
countries. The ndings of this work suggest people without carers may
be experiencing inequitable access to services. This should be investi-
gated further.
Conclusions
This research has shown important new light onto the health and
social care utilisation levels of people with carers. It suggests that such
support may be a key element in enabling individuals to access services
and, as such, there may be wider inequalities in access to services for
people without a carer. Globally our society is ageing. Projections sug-
gest that there will be more people without carers in the future, these
inequalities need to be addressed.
Further research would be benecial to understand differences in
total cost of service use in more depth; including different catego-
risations of people who have a carer, the scale and nature of care
received and longitudinal patterns. Access to health and wellbeing
outcomes would be benecial. This would facilitate a fuller assessment
of the net impact of informal care on an individual’s health and
wellbeing.
CRediT author statement
Jenny Shand: Conceptualization; Data curation; Formal analysis;
Methodology; Writing - Original draft preparation
Manuel Gomes: Methodology; Supervision; Writing - review &
editing.
Steve Morris: Methodology; Supervision; Writing - review & editing.
Funding
This research did not receive any specic grant from funding
agencies in the public, commercial, or not-for-prot sectors
Ethics
This study meets national guidelines set out by the Research Ethics
Service for the NHS in UK. No further ethics approval was required.
(http://www.hra-decisiontools.org.uk/ethics/resultN2.html).
Data sharing
The dataset is not publicly available. It is hosted in the Barking and
Dagenham, Havering and Redbridge NHS Accredited Data Safe Haven
and contains routinely collected, retrospective, pseudonymised data. It
was created for research purposes with ongoing governance and over-
sight provided by the Barking and Dagenham, Havering and Redbridge
Information Governance Steering Committee. Further information
about the dataset is available in the supplementary material.
CRediT authorship contribution statement
J. Shand: Conceptualization, Data curation, Formal analysis,
Methodology, Writing – original draft. M. Gomes: Methodology, Su-
pervision, Writing – review & editing. S. Morris: Methodology, Super-
vision, Writing – review & editing.
J. Shand et al.
Health policy xxx (xxxx) xxx
6
Declaration of interests
We declare no competing interests.
Acknowledgements
This project was supported by the National Institute for Health
Research (NIHR) Applied Research Collaboration (ARC) North Thames
at Bart’s Health NHS Trust. The authors would like to thank UCLPart-
ners, Care City and the Barking and Dagenham analysts who supported
creation of and access to the linked dataset. UCLPartners funded the lead
researchers time but had no involvement in the study or decision to
submit the paper for publication. The views expressed are those of the
author(s) and not necessarily those of the NHS, the NIHR or the
Department of Health and Social Care.
Supplementary materials
Supplementary material associated with this article can be found, in
the online version, at doi:10.1016/j.healthpol.2022.104705.
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